A critical review on the contributions of chemical and physical factors toward the nucleation and growth of large-area graphene

Since the first isolation of graphene over a decade ago, research into graphene has exponentially increased due to its excellent electrical, optical, mechanical and chemical properties. Graphene has been shown to enhance the performance of various electronic devices. In addition, graphene can be simply produced through chemical vapor deposition (CVD). Although the synthesis of graphene has been widely researched, especially the CVD growth method, the lack of understanding of various synthetic parameters still limits the fabrication of large-area and defect-free graphene films. This report critically reviews various parameters affecting the quality of CVD grown graphene to understand the relationship between these parameters and thechoice of metal substrates and to provide a point of reference for future studies of large-area, CVD-grown graphene

Synthesis and Biological Evaluation of some Novel 2-Mercaptobenzothiazoles Carrying 1,3,4-Oxadiazole, 1,3,4-Thiadiazole and 1,2,4-Triazole Moieties

Several 2-mercaptobenzothiazole derivatives containing 1,3,4-oxadiazoles, 1,2,4-triazoles and 1,3,4-thiadiazoles at the second position were synthesized. Some of these synthesized compounds were evaluated for their in vivo analgesic, anti-inflammatory, acute toxicity and ulcerogenic actions. Some of the tested compounds showed significant analgesic and anti-inflammatory activities. Two of the compounds showed significant gastrointestinal protection compared to the standard drug diclofenac sodium. The compounds were also tested for their in vitro antimicrobial activity with most displaying selective activity against the Gram-negative bacteria Pseudomonas aeruginosa. In the present investigation the tested compounds did not possess antifungal activity.Keywords: 2-Mercaptobenzothiazoles, 1,3,4-oxadiazoles, 1,3,4-thiadiazoles, Antimicrobial Activity, Anti-inflammatory Activit

Magnesiothermic Reduction of Silica: A Machine Learning Study

undamental studies have been carried out experimentally and theoretically on the magnesiothermic reduction of silica with different Mg/SiO2 molar ratios (1–4) in the temperature range of 1073 to 1373 K with different reaction times (10–240 min). Due to the kinetic barriers occurring in metallothermic reductions, the equilibrium relations calculated by the well-known thermochemical software FactSage (version 8.2) and its databanks are not adequate to describe the experimental observations. The unreacted silica core encapsulated by the reduction products can be found in some parts of laboratory samples. However, other parts of samples show that the metallothermic reduction disappears almost completely. Some quartz particles are broken into fine pieces and form many tiny cracks. Magnesium reactants are able to infiltrate the core of silica particles via tiny fracture pathways, thereby enabling the reaction to occur almost completely. The traditional unreacted core model is thus inadequate to represent such complicated reaction schemes. In the present work, an attempt is made to apply a machine learning approach using hybrid datasets in order to describe complex magnesiothermic reductions. In addition to the experimental laboratory data, equilibrium relations calculated by the thermochemical database are also introduced as boundary conditions for the magnesiothermic reductions, assuming a sufficiently long reaction time. The physics-informed Gaussian process machine (GPM) is then developed and used to describe hybrid data, given its advantages when describing small datasets. A composite kernel for the GPM is specifically developed to mitigate the overfitting problems commonly encountered when using generic kernels. Training the physics-informed Gaussian process machine (GPM) with the hybrid dataset results in a regression score of 0.9665. The trained GPM is thus used to predict the effects of Mg-SiO2 mixtures, temperatures, and reaction times on the products of a magnesiothermic reduction, that have not been covered by experiments. Additional experimental validation indicates that the GPM works well for the interpolates of the observations.publishedVersio

Array atomic force microscopy for real-time multiparametric analysis.

Nanoscale multipoint structure-function analysis is essential for deciphering the complexity of multiscale biological and physical systems. Atomic force microscopy (AFM) allows nanoscale structure-function imaging in various operating environments and can be integrated seamlessly with disparate probe-based sensing and manipulation technologies. Conventional AFMs only permit sequential single-point analysis; widespread adoption of array AFMs for simultaneous multipoint study is challenging owing to the intrinsic limitations of existing technological approaches. Here, we describe a prototype dispersive optics-based array AFM capable of simultaneously monitoring multiple probe-sample interactions. A single supercontinuum laser beam is utilized to spatially and spectrally map multiple cantilevers, to isolate and record beam deflection from individual cantilevers using distinct wavelength selection. This design provides a remarkably simplified yet effective solution to overcome the optical cross-talk while maintaining subnanometer sensitivity and compatibility with probe-based sensors. We demonstrate the versatility and robustness of our system on parallel multiparametric imaging at multiscale levels ranging from surface morphology to hydrophobicity and electric potential mapping in both air and liquid, mechanical wave propagation in polymeric films, and the dynamics of living cells. This multiparametric, multiscale approach provides opportunities for studying the emergent properties of atomic-scale mechanical and physicochemical interactions in a wide range of physical and biological networks

Compact RFID Enabled Moisture Sensor

This research proposes a novel, low-cost RFID tag sensor antenna implemented using commercially available Kodak photo-paper. The aim of this paper is to investigate the possibility of stable, RFID centric communication under varying moisture levels. Variation in the frequency response of the RFID tag in presence of moisture is used to detect different moisture levels. Combination of unique jaw shaped contours and T-matching network is used for impedance matching which results in compact size and minimal ink consumption. Proposed tag is 1.4x9.4 cm(2) in size and shows optimum results for various moisture levels upto 45 % in FCC band with a bore sight read range of 12.1 m

TAT-peptide conjugated repurposing drug against SARS-CoV-2 main protease (3CLpro): potential therapeutic intervention to combat COVID-19

The Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that originated in Chinese city of Wuhan has caused around 906,092 deaths and 28,040,853 confirmed cases worldwide (WHO, 11 September, 2020). In a life-threatening situation, where there is no specific and licensed anti-COVID-19 vaccine or medicine available; the repurposed drug might act as a silver bullet. Currently, more than 211 vaccines, 80 antibodies, 31 antiviral drugs, 35 cell-based, 6 RNA-based and 131 other drugs are in clinical trials. It is therefore utter need of the hour to develop an effective drug that can be used for the treatment of COVID-19 before a vaccine can be developed. One of the best-characterized and attractive drug targets among coronaviruses is the main protease (3CL^{pro}). Therefore, the current study focuses on the molecular docking analysis of TAT-peptide^{47–57} (GRKKRRQRRRP)-conjugated repurposed drugs (i.e., lopinavir, ritonavir, favipiravir, and hydroxychloroquine) with SARS-CoV-2 main protease (3CL^{pro} to discover potential efficacy of TAT-peptide (TP) - conjugated repurposing drugs against SARS-CoV-2. The molecular docking results validated that TP-conjugated ritonavir, lopinavir, favipiravir, and hydroxychloroquine have superior and significantly enhanced interactions with the target SARS-CoV-2 main protease. In-silico approach employed in this study suggests that the combination of the drug with TP is an excelling alternative to develop a novel drug for the treatment of SARS-CoV-2 infected patients. The development of TP based delivery of repurposing drugs might be an excellent approach to enhance the efficacy of the existing drugs for the treatment of COVID-19. The predictions from the results obtained provide invaluable information that can be utilized for the choice of candidate drugs for in vitro, in vivo and clinical trials. The outcome from this work prove crucial for exploring and developing novel cost-effective and biocompatible TP conjugated anti-SARS-CoV-2 therapeutic agents in immediate future